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Record W1979941066

Clinical Significance of Fever and Leukocytosis in Diagnosis of Acute Appendicitis in Children Who Visit Emergency Department With Abdominal Pain

2012· article· en· W1979941066 on OpenAlexvenueno aff
Sang Hyun Ha, Chong Kun Hong, Young Hwan Lee, Ae Jin Sung, Jun Ho Lee, Kwang Won Cho, Seong Youn Hwang, Na-Kyoung Lee, Hyeon Woo Yim

Bibliographic record

VenueInternational Journal of Clinical Pediatrics · 2012
Typearticle
Languageen
FieldMedicine
TopicAppendicitis Diagnosis and Management
Canadian institutionsnot available
Fundersnot available
KeywordsLeukocytosisMedicineAppendicitisAbdominal painEmergency departmentWhite blood cellMedical recordGeneral surgeryInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Background: The use of fever in the diagnosis of appendicitis in pediatric patients is unproven. The purpose of this investigation was to determine the value of fever in the diagnosis of acute appendicitis in children presenting to the emergency department (ED) with acute abdominal pain. Methods: Medical records from January-December, 2009, were reviewed for children (age < 18 years) who presented to an ED of one medical center with abdominal pain. Data on initial body temperature, white blood cell count, left shift, and final diagnosis were analyzed. Results: Of 674 children, 119 had appendicitis. The prevalance of initial fever did not differ between those with and without appendicitis, but the prevalence of leukocytosis and left shift were higher in children diagnosed with appendicitis. Despite of stratification by age, leukocytosis, prevalence of fever was not differing. Conclusions: Fever does not help in diagnosing appendicitis in our patients. Leukocytosis and white cell left shifts are on the other hand more common in patients with appendicitis. More studies should follow to investigate their role in diagnosis of appendicitis in patients in emergency department.  doi:10.4021/ijcp104e

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.385
Teacher spread0.355 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2012
Admission routes1
Has abstractyes

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